1. Field of Invention
This invention relates to efficiently assembling the meanings of words and phrases in natural language such that both syntactic ambiguity and semantic scope ambiguity can be represented.
2. Description of Related Art
For a single sentence, thousands of syntactic analysis may be available. Similarly, tens of thousands of semantic analyses may also exist for each syntactic analysis. Therefore, the combination of syntactic and semantic ambiguities results in an exponential increase in the number of possible readings for a sentence. Human beings perform an unconscious filtering out of many of these sentence readings. However machine based systems are unable to perform this filtering. Instead, machine based systems must have some representation technique of explicitly representing the syntactic and semantic ambiguity which does not require enumerating the exponentially large number of combinations and which provides for effective processing.
Lexical Functional Grammar uses syntactic structures called functional structures or f-structures to represent individual syntactic analyses. In the Xerox Language Environment, syntactic ambiguity is captured in a single syntactic structure called a packed f-structure by incorporating context variables to show how common substructures are shared between different analyses. The Xerox Language Environment uses packed f-structures to capture lexical and attachment syntactic ambiguity.
However, neither f-structures nor packed f-structures represent semantic information or semantic ambiguity such as semantic quantifier scope ambiguity. Therefore, a technique called Linear Logic Meaning Assembly or Glue Semantics was developed to derive representations of semantic information from f-structures. Substructures within the f-structure contribute premises pairing word meanings with formulas in linear logic. A process of linear logic deduction combines these premises to pair a sentence meaning with the f-structure. Linear Logic Meaning Assembly can derive alternative meanings from a single f-structure constituting a single syntactic analysis of a sentence that exhibits quantifier scope ambiguity and/or other types of semantic ambiguity. Moreover, Linear Logic Meaning Assembly can be used to derive a single, efficient, skeleton-modifier representation of all the possible meanings of a single f-structure constituting a single syntactic analysis of a sentence.
However, the methods used to represent quantifier scope and semantic ambiguity use different features than the methods used to represent syntactic ambiguity. Accordingly, these methods do not lead to the derivation of a single efficient semantic representation representing the combination of all possible syntactic ambiguities with all possible semantic ambiguities. Accordingly, for a given sentence two representation structures are necessary. One representation structure is necessary to represent all possible syntactic ambiguities and another representation structure is necessary to represent all semantic ambiguities.